// Bayesian Network
//   Elvira format 

bnet  "Ejemplo1" { 

// Network Properties

kindofgraph = "directed";
visualprecision = "0.00";
version = 1.0;
default node states = (presente , ausente);

// Variables 

node Enfermedad(finite-states) {
kind-of-node = chance;
type-of-variable = finite-states;
pos_x =130;
pos_y =155;
relevance = 7.0;
purpose = "";
num-states = 2;
states = ("presente" "ausente");
}

node Prueba(finite-states) {
kind-of-node = chance;
type-of-variable = finite-states;
pos_x =454;
pos_y =155;
relevance = 7.0;
purpose = "";
num-states = 2;
states = ("positivo" "negativo");
}

// Links of the associated graph:

link Enfermedad Prueba;

//Network Relationships: 

relation Enfermedad { 
comment = "";
kind-of-relation = potential;
deterministic=false;
values= table (0.08 0.92 );
}

relation Prueba Enfermedad { 
comment = "";
kind-of-relation = potential;
deterministic=false;
values= table (0.75 0.04 0.25 0.96 );
}

}
